liuganghuggingface/moldata-muv

MUV maximum unbiased validation virtual screening

Complete untransformed DeepChem source table for MUV maximum unbiased validation virtual screening. MoleculeNet is a benchmark view of the original experimental or quantum source.

Processed copy of muv from the molecular datasets collection. Structures are canonicalized and validated; labels are never averaged or filled. Prefer the original source for citation.

Where the data comes from

• Original data: published with the original study
• Original study: Rohrer and Baumann. Maximum Unbiased Validation (MUV) Data Sets for Virtual Screening Based on PubChem Bioactivity Data (2009)
• Redistributed by: MoleculeNet (DeepChem) (dataset page)

Data quality

Grade: caution (rough; rules on the hub page).

• info: experiment. Label origin from the source's tags.
• good: valid structures. Rows RDKit cannot parse (kept in quarantine).
• warn: 24% undefined stereo. Molecules with at least one unassigned stereocenter (BACE: 71%).
• info: 5 stereoisomer sets. Groups of stereoisomers in the sampled structures; their labels can differ sharply.
• good: 5% PAINS alerts. Molecules matching PAINS substructures, which often interfere with assays.
• bad: 0.2% minority class. Median share of the rarer class across classification tasks.
• bad: 16% label coverage. Median share of molecules labelled per task; missing labels are unmeasured, not negative.
• good: 14,691 molecules per task. Median molecules with a label per task.

Tables

Config	Splits	Rows	Targets
000_muv	full	93,087	MUV-466 (classification, binary; missing is unmeasured), MUV-548 (classification, binary; missing is unmeasured), MUV-600 (classification, binary; missing is unmeasured), MUV-644 (classification, binary; missing is unmeasured), MUV-652 (classification, binary; missing is unmeasured), MUV-689 (classification, binary; missing is unmeasured), MUV-692 (classification, binary; missing is unmeasured), MUV-712 (classification, binary; missing is unmeasured) and 9 more

data/ holds parseable rows with identical rows collapsed. observations/ holds every source row, including unparseable structures, for auditing. Added columns: SMILES_original, SMILES_canonical (RDKit; stereo, salts, and * kept), structure_key (JSON list of canonical components; use it to deduplicate or group), structure_status, wildcard_atom_count, source_row_first, observation_count, source_dataset, source_table. All original columns are strings, so censored values such as <10 survive; cast labels yourself.

Load

from torch_molecule.datasets import load_dataset
data = load_dataset("muv")

from datasets import load_dataset
ds = load_dataset("liuganghuggingface/moldata-muv", "000_muv")

Known issues

• Constructed benchmark with extremely few actives per assay. Decoy and selection procedures affect applicability; missing labels are not negatives.

License

Not stated by the source. Redistributed with the collection maintainer's approval; check the original source (https://github.com/deepchem/deepchem/blob/master/deepchem/molnet/load_function/muv_datasets.py) for its terms before reuse.

Citation

Cite the original study and data source:

• Rohrer and Baumann. Maximum Unbiased Validation (MUV) Data Sets for Virtual Screening Based on PubChem Bioactivity Data (2009)
• Wu et al. MoleculeNet: a benchmark for molecular machine learning (2018)
• Official DeepChem loader and task definitions